This role places you as an AI Engineer within Bain's Coro team, developing GenAI powered tools and data analytics to support Commercial Excellence. The focus is on LLM driven features, agentic workflows, and delivering production ready AI applications.

Responsibilities

Develop AI powered tools and products that deliver measurable business outcomes.
Design GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern large language model stacks.
Implement agentic workflows with emphasis on reliability, safety, and clear failure modes, including tool usage, multi-step execution, and human in the loop controls.
Design and build advanced search, retrieval, and knowledge pipelines across diverse data stores, covering hybrid search, vector stores, graphs/knowledge graphs, and traditional data platforms, with indexing strategies, metadata design, relevance tuning, freshness, caching, access controls, and source attribution.
Develop robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns.
Integrate AI solutions into enterprise environments and workflows via APIs, data systems, and collaboration tools, balancing quality, latency, cost, privacy, and adoption.
Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
Build and apply data science and machine learning capabilities, delivering end to end ML solutions from data preparation and feature engineering to model selection, training, validation, testing, and performance analysis.
Apply methods spanning classical ML and deep learning, including sequence, text, and image models when relevant.
Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and clear documentation.
Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre training versus post training concepts such as instruction tuning and preference optimization.
Engineer for real delivery by writing clean, testable, maintainable code and shipping AI services through the full software development lifecycle: build, test, deploy, monitor, and iterate.
Implement MLOps and GenAIOps practices, including CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness.
Build evaluation and observability for GenAI and agented systems, including tracing, instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt and policy optimization.
Design for secure enterprise deployment with access controls, auditability, handling of sensitive and PII data, and responsible AI guardrails.
Create reusable components and accelerators such as templates, evaluation harnesses, connectors, and orchestration patterns that scale across client contexts.
Thrive in a client facing consulting environment by communicating clearly with technical and non-technical stakeholders, leading working sessions, presenting recommendations, and producing concise technical documentation.
Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value and support proposal shaping and scoping, including effort sizing, architecture options, risk assessment, and delivery roadmaps.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
3–5+ years of professional AI / ML engineering experience with strong backend fundamentals.
Strong Python proficiency and experience building APIs / services (REST or gRPC) and integrating with enterprise systems.
Hands-on experience delivering LLM powered applications with attention to latency, cost, reliability, and security.
Experience building advanced retrieval and search systems (hybrid retrieval, vector search, reranking) and working across multiple data stores (vector, graph, relational, document, and search platforms).
Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (eg, LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops, and sound judgment on when to apply agentic approaches.
Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation to enforce reliable data contracts.
Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling.
Experience deploying and operating services on AWS, GCP, or Azure (environment management, reliability, observability, scaling).
Experience with Docker and Kubernetes (or equivalent orchestration) and operating services in production (debugging, performance, resilience).
Proven ability to implement security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls).
Experience training, validating, and testing ML models; strong understanding of overfitting, generalization, and evaluation methodology.
Practical experience with feature engineering and data preprocessing for real world datasets.
Familiarity with a broad set of ML algorithms (classical ML and deep learning) and ability to choose methods appropriate to business and data constraints.
Familiarity with deep learning frameworks (PyTorch or TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
Proven ability to operate in ambiguity and complexity, manage competing priorities, and deliver outcomes independently or with a team.
Excellent interpersonal and communication skills, with the ability to explain technical decisions, tradeoffs, and results to mixed audiences.
Strong stakeholder management skills and comfort working directly with clients.

Technologies

Python
REST, gRPC
LangGraph
OpenAI Agents SDK
Pydantic AI
PyTorch, TensorFlow
Docker, Kubernetes
AWS, GCP, Azure
MCP
Graph databases

Benefits

Bain pays 100 percent of individual employee premiums for medical, dental, and vision coverage.
Generous paid time off including parental leave, sick leave, and holidays.
Fully vested 401(k) company contribution.
Paid life and long-term disability insurance.
Annual fitness reimbursements.

What makes us a great place to work

We are consistently recognized as a leading employer in the global market, including top rankings on Glassdoor. Exceptional teams drive our strategy, and we foster an inclusive environment that welcomes diverse backgrounds, cultures, and experiences. We hire talented individuals and create conditions for professional and personal growth.

U.S. Compensation Information

In the states listed (Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, California), the good faith annualized full-time salary range for this role is $128,500 to $171,500; placement within the range varies by experience, education, and other factors.
The role includes an annual discretionary performance bonus.
4.5% 401(k) company contribution, which increases after three years of service and is 100% vested from the start date.
Some elements of discretionary compensation may apply beyond the base and bonus.
For locations outside the listed states, compensation is commensurate with competitive geographic market rates.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.

Expert Consultant, Coro, AI Engineer